• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.543-553
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• 2011

Sea ice concentration calculated from the AMSR-E onboard Aqua satellite by using NASA Team2 sea ice algorithm has proven to be very accurate over sea ice in Antarctic Ocean. When glacial ice such as icebergs and ice shelves are dominant in an AMSR-E footprint, the accuracy of the ice concentration calculated from NASA Team2 algorithm is not well maintained due to the different microwave characteristics of the glacial ice from sea ice. We extracted the concentrations of sea ice and glacial ice from two ENVISAT ASAR images of George V coast in southern Antarctica, and compared them with NASA Team2 sea ice concentration. The result showed that the NASA Team2 algorithm underestimates the concentration of glacial ice. To interpret the large deviation of estimation over glacial ice, we analyzed the characteristics of microwave radiation of the glacial ice in PR(polarization ratio), GR(spectral gradient ratio), $PR_R$(rotated PR), and ${\Delta}GR$ domain. We found that glacial ice occupies a unique region in the PR, GR, $PR_R$, and ${\Delta}GR$ domain different from other types of ice such as ice type A, B, and C, and open water. This implies that glacial ice can be added as a new category of ice to the AMSR-E NASA Team2 sea ice algorithm.

• The Bulletin of The Korean Astronomical Society
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• v.34 no.1
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• pp.143-143
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• 2009

• Journal of Astronomy and Space Sciences
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• v.40 no.2
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• pp.79-88
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• 2023

On Aug. 4, 2022, at 23:08:48 (UTC), the Korea Pathfinder Lunar Orbiter (KPLO), also known as Danuri, was launched using a SpaceX Falcon 9 launch vehicle. Currently, KPLO is successfully conducting its science mission around the Moon. The National Aeronautics and Space Administration (NASA)'s Deep Space Network (DSN) was utilized for the successful flight operation of KPLO. A great deal of joint effort was made between the Korea Aerospace Research Institute (KARI) and NASA DSN team since the beginning of KPLO ground system design for the success of the mission. The efficient utilization and management of NASA DSN in deep space exploration are critical not only for the spacecraft's telemetry and command but also for tracking the flight dynamics (FD) operation. In this work, the top-level DSN interface architecture, detailed workflows, DSN support levels, and practical lessons learned from the joint team's efforts are presented for KPLO's successful FD operation. Due to the significant joint team's efforts, KPLO is currently performing its mission smoothly in the lunar mission orbit. Through KPLO cooperative operation experience with DSN, a more reliable and efficient partnership is expected not only for Korea's own deep space exploration mission but also for the KARI-NASA DSN joint support on other deep space missions in the future.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.64.2-64.2
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• 2010

From 2009, CEOU of Seoul National University has been utilizing the United Kingdom Infrared Telescope (UKIRT) at Mauna Kea, Hawaii, as one of its research facilities. UKIRT is a telescope with 3.8m primary mirror, and it is currently the largest telescope specialized for infrared observations. We will summarize our research activities using UKIRT, which include Infrared Medium-deep Survey (IMS) of proto-clusters and high redshift quasars, NIR imaging programs of Gamma Ray Bursts (GRBs), Gamma Ray sources, and SNUQSO quasars. Our research programs include international collaboration with the UK GRB team, the NASA/Swift team, Pomona College, and National Central University of Taiwan. We will also touch on our future plan of using UKIRT.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.8-13
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• 2007

2005년 남극의 해빙을 촬영한 Kompsat-1 EOC 영상을 이용하여 SSM/I와 AMSR-E 해빙 면적비를 비교， 분석하였다. EOC 영상은 남극의 봄철에 해당하는 9-11월 사이에 남극 대륙의 가장자리를 가로지르는 11 개 궤도로부터 총 676개 영상이 획득되었으며， 이 중 대기 및 광량 조건이 양호한 68개 의 영상을 선별하였다. EOC 영상에 감독분류 방볍 을 적 용하여 표면 유형 을 White ice(W), Grey ice(G), Dark-grey ice(D), Ocean(O)로 분류하였고 해빙 면적비를 산출하였으며, 이를 NASA Team Algorithm(NT)으로 계산된 SSM/I 해빙 면적비, NASA Team2 Algorithm(NT2)으로 계산된 AMSR-E 해빙 면적비와 비교하였다. 남극의 봄철에 SSM/I 해빙 면적비는 EOC W+G 면적비와 잘 일치하였고，AMSR-E 해빙 면적비는 EOC W+G+D 면적비와 좋은 상관성을 나타내었다. 따라서 이 시기의 남극 SSM/I NT 해빙 면적비는 W와 G만을 반영하며, AMSR-E NT2 해빙 면적비는 D도 포함하는 것을 알 수 있었다. 또한 AMSR-E가 SSM/I보다 높은 해빙 면적비를 나타내는 것을 확인하였으며，두 수동 마이크로파 해빙 면적비의 차이는 EOC D 면적비와 높은 상관성을 보였다. 이로부터 EOC 영상에서 분류된 D와 NT2에 서 고려되는 Ice type C가 서로 유사한 해빙 유형임을 추정할 수 있었다.

• Journal of computational fluids engineering
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• v.22 no.1
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• pp.8-14
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• 2017

In this paper, separated flow characteristics is studied using the RANS(Reynold-averaged Navier-Stokes) modeling. The analysis is performed for the NASA's hump configuration which is the combination of a flat plate and a hump. This configuration was used in NASA's flow control workshop and it was one of validation cases for RANS and LES simulations. The separation occurs at the 65% of model length where a slot is positioned for the flow control. No flow control case and steady suction case are studied using RANS modeling. The Spalart-Allmaras model and the SST(Shear Stress Transport) model are applied and their accuracy are compared. To correlate CFD analysis with experimental data, the optimal boundary condition was investigated and the effect of a cavity around the slot is studied for the no flow case.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.507-520
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• 2007

Satellite passive microwave(PM) sensors have been observing polar sea ice concentration(SIC), ice temperature, and snow depth since 1970s. Among them SIC is playing an important role in the various studies as it is considered the first factor for the monitoring of global climate and environment changes. Verification and correction of PM SIC is essential for this purpose. In this study, we calculated SIC from KOMPSAT-1 EOC images obtained from Arctic sea ice edges from July to August 2005 and compared with SSM/I SIC calculated from NASA Team(NT) algorithm. When we have no consideration of sea ice types, EOC and SSM/I NT SIC showed low correlation coefficient of 0.574. This is because there are differences in spatial resolution and observing time between two sensors, and the temporal and spatial variation of sea ice was high in summer Arctic ice edge. For the verification of SSM/I NT SIC according to sea ice types, we divided sea ice into land-fast ice, pack ice, and drift ice from EOC images, and compared them with SSM/I NT SIC corresponding to each ice type. The concentration of land-fast ice between EOC and SSM/I SIC were calculated very similarly to each other with the mean difference of 0.38%. This is because the temporal and spatial variation of land-fast ice is small, and the snow condition on the ice surface is relatively dry. In case of pack ice, there were lots of ice ridge and new ice that are known to be underestimated by NT algorithm. SSM/I NT SIC were lower than EOC SIC by 19.63% in average. In drift ice, SSM/I NT SIC showed 20.17% higher than EOC SIC in average. The sea ice with high concentration could be included inside the wide IFOV of SSM/I because the drift ice was located near the edge of pack ice. It is also suggested that SSM/I NT SIC overestimated the drift ice covered by wet snow.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.35.4-35.4
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• 2021

The Double Asteroid Redirection Test (DART) is NASA's first planetary defense test mission, designed to test the kinetic deflector technique by crashing into an asteroid and changing its orbit. DART's launch window opens in November, 2021, with arrival at its target less than a year later in late September or early October 2022. The target of the DART spacecraft is the moonlet Dimorphos, a 150-m moonlet orbiting the 780-m asteroid Dimorphos. By changing the orbit of Dimorphos around Didymos, the results can be detected much more easily than changing the orbit of an asteroid around the Sun. I will discuss what we know about Didymos and Dimorphos, the plans for the DART mission, the expected results, and how DART is important for planetary defense in general.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.1 s.39
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• pp.23-29
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• 2007

Spatial outliers in remotely sensed imagery represent observed quantities showing unusual values compared to their neighbor pixel values. There have been various methods to detect the spatial outliers based on spatial autocorrelations in statistics and data mining. These methods may be applied in detecting forest fire pixels in the MODIS imageries from NASA's AQUA satellite. This is because the forest fire detection can be referred to as finding spatial outliers using spatial variation of brightness temperature. In this paper, we propose a new forest fire detection algorithm which is based on local spatial association analysis, and test the proposed algorithm to evaluate its applicability. In order to evaluate the proposed algorithm, the results were compared with the MODIS fire product provided by the NASA MODIS Science Team, which showed the possibility of the proposed algorithm in detecting the fire pixels.

• Composites Research
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• v.34 no.5
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• pp.283-289
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• 2021

This paper derives numerically the buckling Knockdown factors using two different initial imperfection models, such as geometric and loading imperfection models, to investigate the unstiffened composite cylinder with an ellipse pre-buckling deformation pattern. Single Perturbation Load Approach (SPLA) is applied to represent the geometric initial imperfection of a thin-walled composite cylinder; while Single Boundary Perturbation Approach (SBPA) is used to represent the geometric and loading imperfections simultaneously. The buckling Knockdown factor derived using SPLA is higher than NASA's buckling design criteria by approximately 84%, and lower than buckling test result by 9%. The buckling Knockdown factor using SBPA is higher than NASA's buckling design criteria by about 75%, and 14% lower than the buckling test result. Therefore, it is shown that the buckling Knockdown factors derived in this study can provide a lightweight design compared to the previous buckling design criteria while they give reasonably a conservative design compared to the buckling test for both the initial imperfection models.